{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hybrid Auto and AStar"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creates 3 transmon pockets in an L shape, each of which can be rotated in increments of 90 deg.\n",
    "Anchors are user-specified points through which the CPW must pass.\n",
    "For a specified step size and suitable choice of anchors, a snapped path can always be found.\n",
    "How close this path is to the shortest path depends on the step size - a smaller step size generally yields more optimal paths but requires a longer runtime."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Preparations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next cell enables [module automatic reload](https://ipython.readthedocs.io/en/stable/config/extensions/autoreload.html?highlight=autoreload). Your notebook will be able to pick up code updates made to the qiskit-metal (or other) module code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import key libraries and open the Metal GUI. Also we configure the notebook to enable overwriting of existing components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit_metal import designs, draw\n",
    "from qiskit_metal import MetalGUI, Dict\n",
    "\n",
    "design = designs.DesignPlanar()\n",
    "gui = MetalGUI(design)\n",
    "\n",
    "# If you disable the next line, then you will need to delete a component [<component>.delete()] before recreating it.\n",
    "design.overwrite_enabled = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create 3 transmon qubits with 4 pins. This uses the same definition (options) for all 3 qubits, but it places them in 3 different (x,y) origin points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from qiskit_metal.qlibrary.qubits.transmon_pocket import TransmonPocket\n",
    "\n",
    "options = dict(\n",
    "    pad_width = '425 um', \n",
    "    pocket_height = '650um',\n",
    "    connection_pads=dict(  # pin connectors\n",
    "        a = dict(loc_W=+1,loc_H=+1), \n",
    "        b = dict(loc_W=-1,loc_H=+1, pad_height='30um'),\n",
    "        c = dict(loc_W=+1,loc_H=-1, pad_width='200um'),\n",
    "        d = dict(loc_W=-1,loc_H=-1, pad_height='50um')\n",
    "    )\n",
    ")\n",
    "\n",
    "q0 = TransmonPocket(design, 'Q0', options = dict(pos_x='-1.0mm', pos_y='-1.0mm', **options))\n",
    "q1 = TransmonPocket(design, 'Q1', options = dict(pos_x='1.0mm', pos_y='+0.0mm', **options))\n",
    "q2 = TransmonPocket(design, 'Q2', options = dict(pos_x='-1.0mm', pos_y='0.0mm', **options))\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the RoutePathfinder class and inspect what options are available for you to initialize."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'pin_inputs': {'start_pin': {'component': '', 'pin': ''},\n",
       "  'end_pin': {'component': '', 'pin': ''}},\n",
       " 'fillet': '0',\n",
       " 'lead': {'start_straight': '0mm',\n",
       "  'end_straight': '0mm',\n",
       "  'start_jogged_extension': '',\n",
       "  'end_jogged_extension': ''},\n",
       " 'total_length': '7mm',\n",
       " 'chip': 'main',\n",
       " 'layer': '1',\n",
       " 'trace_width': 'cpw_width',\n",
       " 'anchors': {},\n",
       " 'advanced': {'avoid_collision': 'true'},\n",
       " 'step_size': '0.25mm',\n",
       " 'hfss_wire_bonds': False,\n",
       " 'q3d_wire_bonds': False}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit_metal.qlibrary.tlines.pathfinder import RoutePathfinder\n",
    "RoutePathfinder.get_template_options(design)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we've set the fillet radius to be 90 microns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ops=dict(fillet='90um')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the 3-qubit arrangement from before, our goal is to connect pins on two of them. Moreover, we want some degree of control over how that path is constructed.\n",
    "This is where anchors come into play. Anchors are predefined points in space that the path must cross. They are stored in an ordered dictionary data structure that maps the\n",
    "anchor number to a numpy array of length 2. The anchor number is an integer, starting at 0, that determines that anchor point's position relative to the start pin; larger\n",
    "anchor numbers are farther along the path. The numpy array stores the x and y coordinates of the anchor.\n",
    "\n",
    "For this and the subsequent examples, we have chosen a step size of 0.25 mm, which means that the algorithm searches for valid paths to the next anchor point in increments\n",
    "of that amount. Valid paths do not collide with other components or self-intersect. The start and end pins are labelled by their component and component-specific pin, in\n",
    "this case Q0_b and Q1_b."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from collections import OrderedDict\n",
    "\n",
    "anchors = OrderedDict()\n",
    "anchors[0] = np.array([0.048, -0.555])\n",
    "anchors[1] = np.array([0.048, 0.195])\n",
    "\n",
    "options = {'pin_inputs': \n",
    "            {'start_pin': {'component': 'Q0', 'pin': 'b'}, \n",
    "             'end_pin': {'component': 'Q1', 'pin': 'b'}},\n",
    "            'lead': {'start_straight': '91um', 'end_straight': '90um'},\n",
    "            'step_size': '0.25mm',\n",
    "            'anchors': anchors,\n",
    "            **ops\n",
    "           }\n",
    "\n",
    "qa = RoutePathfinder(design, 'line', options)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The current algorithm can only allow 1 such CPW to be built at a time, thus we delete old CPWs before building new ones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "design.delete_component('line')\n",
    "\n",
    "gui.rebuild()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's try wrapping the CPW around the outer edge of the bottom left qubit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "anchors = OrderedDict()\n",
    "anchors[0] = np.array([-0.452, -0.555])\n",
    "anchors[1] = np.array([-0.452, -1.5])\n",
    "anchors[2] = np.array([0.048, -1.5])\n",
    "\n",
    "options = {'pin_inputs': \n",
    "            {'start_pin': {'component': 'Q0', 'pin': 'b'}, \n",
    "             'end_pin': {'component': 'Q1', 'pin': 'b'}},\n",
    "            'lead': {'start_straight': '91um', 'end_straight': '90um'},\n",
    "            'step_size': '0.25mm',\n",
    "            'anchors': anchors,\n",
    "            **ops\n",
    "           }\n",
    "\n",
    "qa = RoutePathfinder(design, 'line', options)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "design.delete_component('line')\n",
    "\n",
    "gui.rebuild()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also try switching around the components/pins and not specifying any anchor points to see what happens."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "options = {'pin_inputs': \n",
    "            {'start_pin': {'component': 'Q0', 'pin': 'a'}, \n",
    "             'end_pin': {'component': 'Q2', 'pin': 'd'}},\n",
    "            'lead': {'start_straight': '90um', 'end_straight': '90um'},\n",
    "            'step_size': '0.25mm',\n",
    "            **ops\n",
    "          }\n",
    "\n",
    "qa = RoutePathfinder(design, 'line', options)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "design.delete_component('line')\n",
    "\n",
    "gui.rebuild()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or we can specify even more anchor points!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "anchors = OrderedDict()\n",
    "anchors[0] = np.array([-2, 0.5])\n",
    "anchors[1] = np.array([0, 0.5])\n",
    "anchors[2] = np.array([0, -1])\n",
    "anchors[3] = np.array([2, -1])\n",
    "\n",
    "options = {'pin_inputs': \n",
    "            {'start_pin': {'component': 'Q0', 'pin': 'd'}, \n",
    "             'end_pin': {'component': 'Q1', 'pin': 'c'}},\n",
    "            'step_size': '0.25mm',\n",
    "            'anchors': anchors,\n",
    "            **ops\n",
    "           }\n",
    "\n",
    "qc = RoutePathfinder(design, 'line', options)\n",
    "\n",
    "gui.rebuild()\n",
    "gui.autoscale()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gui.screenshot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODOs:\n",
    "\n",
    "1. CPW bounding boxes are not well-defined and cannot overlap right now. Bounding boxes should occupy as little\n",
    "area as possible to maximize space for other components.\n",
    "    Example: Connecting Q0_a and Q1_b ought to yield an S-shaped CPW but doesn't because there's supposedly a\n",
    "    bounding box with 0 area centered at the origin (0, 0).\n",
    "2. Rebuilding distorts previously well-defined CPWs.\n",
    "    Example: Connect Q0_a, Q1_c, then connect Q1_b and Q0_d.\n",
    "3. Enable anchor revision via the GUI.\n",
    "4. Save a persistent state in the design so that rebuilding doesn't waste time."
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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